Performance evaluation of a new end-to-end traffic-aware routing in MANETs

There has been a lot of research effort on developing reactive routing algorithms for mobile ad hoc networks (MANETs) over the past few years. Most of these algorithms consider finding the shortest path from source to destination in building a route. However, this can lead to some network nodes being more overloaded than the others. In MANETs resources, such as node power and channel bandwidth are often at a premium and, therefore, it is important to optimise their use as much as possible. Consequently, a traffic-aware technique to distribute the load is very desirable in order to make good utilisation of nodes' resources. Therefore a number of end-to-end traffic aware techniques have been proposed for reactive routing protocols to deal with this challenging issue. In this paper we contribute to this research effort by proposing a new traffic aware technique that can overcome the limitations of the existing methods. Results from an extensive comparative evaluation show that the new technique has superior performance over similar existing end-to-end techniques in terms of the achieved throughput, end-to-end delay and routing overhead

Robustness, Security and Privacy in Location-Based Services for Future IoT : A Survey

Internet of Things (IoT) connects sensing devices to the Internet for the purpose of exchanging information. Location information is one of the most crucial pieces of information required to achieve intelligent and context-aware IoT systems. Recently, positioning and localization functions have been realized in a large amount of IoT systems. However, security and privacy threats related to positioning in IoT have not been sufficiently addressed so far. In this paper, we survey solutions for improving the robustness, security, and privacy of location-based services in IoT systems. First, we provide an in-depth evaluation of the threats and solutions related to both global navigation satellite system (GNSS) and non-GNSS-based solutions. Second, we describe certain cryptographic solutions for security and privacy of positioning and location-based services in IoT. Finally, we discuss the state-of-the-art of policy regulations regarding security of positioning solutions and legal instruments to location data privacy in detail. This survey paper addresses a broad range of security and privacy aspects in IoT-based positioning and localization from both technical and legal points of view and aims to give insight and recommendations for future IoT systems providing more robust, secure, and privacy-preserving location-based services.Peer reviewe

ST-Hadoop: A MapReduce Framework for Big Spatio-temporal Data Management

University of Minnesota Ph.D. dissertation.May 2019. Major: Computer Science. Advisor: Mohamed Mokbel. 1 computer file (PDF); x, 123 pages.Apache Hadoop, employing the MapReduce programming paradigm, that has been widely accepted as the standard framework for analyzing big data in distributed environments. Unfortunately, this rich framework was not genuinely exploited towards processing large scale spatio-temporal data, especially with the emergence and popularity of applications that create them in large-scale. The huge volumes of spatio-temporal data come from applications, like Taxi fleet in urban computing, Asteroids in astronomy research studies, animal movements in habitat studies, neuron analysis in neuroscience research studies, and contents of social networks (e.g., Twitter or Facebook). Managing space and time are two fundamental characteristics that raised the demand for processing spatio-temporal data created by these applications. Besides the massive size of data, the complexity of shapes and formats associated with these data raised many challenges in managing spatio-temporal data. The goal of the dissertation is centered on establishing a full-fledged big spatio-temporal data management system that serves the need for a wide range of spatio-temporal applications. This involves indexing, querying, and analyzing spatio-temporal data. We propose ST-Hadoop; the first full-fledged open-source system with native support for big spatio-temporal data, available to download http://st-hadoop.cs.umn.edu/. ST- Hadoop injects spatio-temporal data awareness inside the highly popular Hadoop system that is considered state-of-the-art for off-line analysis of big data systems. Considering a distributed environment, we focus on the following: (1) indexing spatio-temporal data and (2) Supporting various fundamental spatio-temporal operations, such as range, kNN, and join (3) Supporting indexing and querying trajectories, which is considered as a special class of spatio-temporal data that require special handling. Throughout this dissertation, we will touch base on the background and related work, motivate for the proposed system, and highlight our contributions

Enhancing productivity and performance portability of opencl applications on heterogeneous systems using runtime optimizations

Initially driven by a strong need for increased computational performance in science and engineering, heterogeneous systems have become ubiquitous and they are getting increasingly complex. The single processor era has been replaced with multi-core processors, which have quickly been surrounded by satellite devices aiming to increase the throughput of the entire system. These auxiliary devices, such as Graphics Processing Units, Field Programmable Gate Arrays or other specialized processors have very different architectures. This puts an enormous strain on programming models and software developers to take full advantage of the computing power at hand. Because of this diversity and the unachievable flexibility and portability necessary to optimize for each target individually, heterogeneous systems remain typically vastly under-utilized. In this thesis, we explore two distinct ways to tackle this problem. Providing automated, non intrusive methods in the form of compiler tools and implementing efficient abstractions to automatically tune parameters for a restricted domain are two complementary approaches investigated to better utilize compute resources in heterogeneous systems. First, we explore a fully automated compiler based approach, where a runtime system analyzes the computation flow of an OpenCL application and optimizes it across multiple compute kernels. This method can be deployed on any existing application transparently and replaces significant software engineering effort spent to tune application for a particular system. We show that this technique achieves speedups of up to 3x over unoptimized code and an average of 1.4x over manually optimized code for highly dynamic applications. Second, a library based approach is designed to provide a high level abstraction for complex problems in a specific domain, stencil computation. Using domain specific techniques, the underlying framework optimizes the code aggressively. We show that even in a restricted domain, automatic tuning mechanisms and robust architectural abstraction are necessary to improve performance. Using the abstraction layer, we demonstrate strong scaling of various applications to multiple GPUs with a speedup of up to 1.9x on two GPUs and 3.6x on four

A framework for real time collaborative editing in a mobile replicated architecture

Mobile collaborative work is a developing sub-area of Computer Supported Collaborative Work (CSCW). The future of this field will be marked by a significant increase in mobile device usage as a tool for co-workers to cooperate, collaborate and work on a shared workspace in real-time to produce artefacts such as diagrams, text and graphics regardless of their geographical locations. A real-time collaboration editor can utilise a centralised or a replicated architecture. In a centralised architecture, a central server holds the shared document as well as manages the various aspects of the collaboration, such as the document consistency, ordering of updates, resolving conflicts and the session membership. Every user's action needs to be propagated to the central server, and the server will apply it to the document to ensure it results in the intended document state. Alternatively, a decentralised or replicated architecture can be used where there is no central server to store the shared document. Every participating site contains a copy of the shared document (replica) to work on separately. Using this architecture, every user's action needs to be broadcast to all participating sites so each site can update their replicas accordingly. The replicated architecture is attractive for such applications, especially in wireless and ad-hoc networks, since it does not rely on a central server and a user can continue to work on his or her own local document replica even during disconnection period. However, in the absence of a dedicated server, the collaboration is managed by individual devices. This presents challenges to implement collaborative editors in a replicated architecture, especially in a mobile network which is characterised by limited resource reliability and availability. This thesis addresses challenges and requirements to implement group editors in wireless ad-hoc network environments where resources are scarce and the network is significantly less stable and less robust than wired fixed networks. The major contribution of this thesis is a proposed framework that comprises the proposed algorithms and techniques to allow each device to manage the important aspects of collaboration such as document consistency, conflict handling and resolution, session membership and document partitioning. Firstly, the proposed document consistency algorithm ensures the document replicas held by each device are kept consistent despite the concurrent updates by the collaboration participants while taking into account the limited resource of mobile devices and mobile networks. Secondly, the proposed conflict management technique provides users with conflict status and information so that users can handle and resolve conflicts appropriately. Thirdly, the proposed membership management algorithm ensures all participants receive all necessary updates and allows users to join a currently active collaboration session. Fourthly, the proposed document partitioning algorithm provides flexibility for users to work on selected parts of the document and reduces the resource consumption. Finally, a basic implementation of the framework is presented to show how it can support a real time collaboration scenario

Advances in knowledge discovery and data mining Part II

19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II</p

Proceedings of the 4th International Conference on Principles and Practices of Programming in Java

This book contains the proceedings of the 4th international conference on principles and practices of programming in Java. The conference focuses on the different aspects of the Java programming language and its applications